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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
mgrno: string
permco: string
fdate: timestamp[s]
shares: double
price: double
dollar_holding: double
quarter: string
year: int64
qtr: int64
-- schema metadata --
huggingface: '{"info": {"features": {"mgrno": {"dtype": "string", "_type"' + 414
to
{'permco': Value(dtype='string', id=None), 'embedding': Sequence(feature=Value(dtype='float32', id=None), length=32, id=None)}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1855, in _prepare_split_single
for _, table in generator:
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 690, in wrapped
for item in generator(*args, **kwargs):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/arrow/arrow.py", line 76, in _generate_tables
yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/arrow/arrow.py", line 59, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
mgrno: string
permco: string
fdate: timestamp[s]
shares: double
price: double
dollar_holding: double
quarter: string
year: int64
qtr: int64
-- schema metadata --
huggingface: '{"info": {"features": {"mgrno": {"dtype": "string", "_type"' + 414
to
{'permco': Value(dtype='string', id=None), 'embedding': Sequence(feature=Value(dtype='float32', id=None), length=32, id=None)}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1431, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 992, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1898, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
permco
string | embedding
sequence |
|---|---|
1249 | [
0.022636735811829567,
-0.03247649595141411,
0.07830594480037689,
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0.00794393289834261,
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0.020319979637861252,
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0.003581503638997674,
0.07247315347194672,
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0.010038148611783981,
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0.016160113736987114,
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0.04543628171086311,
0.01597105711698532,
0.01912747509777546,
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0.05455624312162399,
0.021556679159402847,
-0.005160351283848286
]
|
1962 | [
0.009438373148441315,
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0.004308728035539389,
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]
|
20010 | [
0.016762245446443558,
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0.025513313710689545,
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0.012103341519832611
]
|
20017 | [
0.07067360728979111,
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0.012606987729668617
]
|
20030 | [
0.04322746396064758,
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0.05214497447013855,
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0.06716200709342957,
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0.016351258382201195,
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]
|
20060 | [
0.06127915903925896,
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0.06265068799257278,
0.01894315518438816
]
|
20063 | [
0.0529160350561142,
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]
|
20086 | [
0.08818195015192032,
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]
|
20103 | [
0.11132872104644775,
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]
|
20191 | [
0.10238376259803772,
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]
|
20207 | [
0.028571823611855507,
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]
|
20227 | [
0.10444985330104828,
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]
|
20258 | [
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|
20277 | [
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|
20306 | [
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]
|
20327 | [
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0.0037453353870660067
]
|
20350 | [
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End of preview.
YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
US Institutional 13F Holdings Record-level Embeddings Dataset (Merged Quarterly Snapshots 1980–2024)
This dataset provides a single merged Hugging Face DatasetDict combining all 179 quarterly snapshots of U.S. institutional 13F filings (1980 Q1 → 2024 Q3).
Every quarter’s folder has been concatenated into three splits:
- holdings (113,114,724 rows): record-level positions with fields: • mgrno (string) – Institutional manager ID (SEC) • permco (string) – Permanent company identifier • fdate (timestamp[s]) – Quarter-end report date • shares (float64) – Shares held • price (float64) – Price per share on fdate • dollar_holding (float64) – Market value (shares × price)
- asset_embeddings (919,599 rows): PERMCO-level 32-dimensional vectors • permco (string) – PERMCO identifier • embedding (float32[32]) – Asset embedding vector
- investor_embeddings (445,036 rows): manager-level 32-dimensional vectors • mgrno (string) – Institutional manager ID • embedding (float32[32]) – Investor embedding vector
Quick Load Example:
from datasets import load_dataset
ds = load_dataset("kurry/institutional-holdings-13f-quarterly")
print({s: ds[s].num_rows for s in ds}) # {'holdings': 113114724, 'asset_embeddings': 919599, 'investor_embeddings': 445036}
print(ds["holdings"][0])
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